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Real-Time HVAC Sensor Monitoring and Automatic Fault Detection System

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Sensors for Everyday Life

Part of the book series: Smart Sensors, Measurement and Instrumentation ((SSMI,volume 23))

Abstract

Real-time monitoring of heating, ventilation, and air conditioning (HVAC) systems is crucial to maintaining optimal performance such as providing thermal comfort and acceptable indoor air quality, guaranteeing energy saving, and assuring system reliability. In a realistic situation, HVAC systems can degrade in performance or even fail due to a variety of operational problems, such as stuck open or closed air dampers and water valves, supply or exhaust air fan faults, hot or chilled water pump faults, and inefficiencies in the way HVAC systems or pieces of equipemnt are controlled. This paper presents automatic fault detection techniques, as well as a key sensor sets selection approach that can help to maintain the performance of HVAC systems, and optimise fault detection results. One key step to make sure the approach succeeds is the sensor feature selection process. This paper implements the ensemble rapid centroid estimation (ERCE) as the data-driven sensor and feature selection algorithm, which is the core method to assure the automatic fault detection can function correctly. Instead of choosing sensors manually, ERCE method can automatically select representative features that are unique and relevant to the faults in a HVAC system. The methodology presented is implemented in real-world commercial buildings with experimental results showing that different types of faults are detected successfully.

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Author information

Authors and Affiliations

  1. Data61, CSIRO (Commonwealth Scientific and Industrial Research Organisation), Marsfield, NSW, 2122, Australia

    Ying Guo & Jiaming Li

  2. Energy, CSIRO (Commonwealth Scientific and Industrial Research Organisation), Mayfield West, NSW, 2304, Australia

    Josh Wall & Sam West

Authors
  1. Ying Guo
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  2. Josh Wall
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  3. Jiaming Li
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  4. Sam West
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Corresponding author

Correspondence to Ying Guo .

Editor information

Editors and Affiliations

  1. Department of Engineering, Faculty of Science and Engineering, Macquarie University , Sydney, New South Wales, Australia

    Subhas Chandra Mukhopadhyay

  2. Instituto de Telecomunicações , Lisbon, Portugal

    Octavian Adrian Postolache

  3. Massey University , Palmerston North, New Zealand

    Krishanthi P. Jayasundera

  4. Auckland University , Auckland, New Zealand

    Akshya K. Swain

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Guo, Y., Wall, J., Li, J., West, S. (2017). Real-Time HVAC Sensor Monitoring and Automatic Fault Detection System. In: Mukhopadhyay, S., Postolache, O., Jayasundera, K., Swain, A. (eds) Sensors for Everyday Life. Smart Sensors, Measurement and Instrumentation, vol 23. Springer, Cham. https://doi.org/10.1007/978-3-319-47322-2_3

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  • DOI: https://doi.org/10.1007/978-3-319-47322-2_3

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-47321-5

  • Online ISBN: 978-3-319-47322-2

  • eBook Packages: EngineeringEngineering (R0)

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